Programming parallel machines as effectively as sequential ones would ideally require a language that provides high-level programming constructs in order to avoid the programming errors frequent when expressing parallelism. Since task parallelism is often considered more error-prone than data parallelism, we survey six popular and efficient parallel programming languages that tackle this difficult issue: Cilk, Chapel, X10, Habanero-Java, OpenMP and OpenCL. Using as single running example a parallel implementation of the computation of the Mandelbrot set, this paper describes how the fundamentals of task parallel programming, namely collective and point-to-point synchronization and mutual exclusion, are dealt with in these languages. Our study suggests that, even though there is a wealth of various names and notions introduced by these languages, they all boil down to three key task concepts: creation, synchronization and atomicity. The paper is designed to give users and language and compiler designers an overview of current parallel languages.

Email address protected by JavaScript. Activate javascript to see the email.

We use cookies to improve our service for you. You can find more information in our data protection declaration. By continuing to use our site, you accept our use of cookies and Privacy Policy.OkPrivacy policy